This paper presents an incremental approach to understanding 3D structure and motion of rigid as well as nonrigid objects from image sequences. To be applicable to natural imagery like TV signals, the recovery process should meet two requirements: robustness to noise and ability of coping with deformable objects. These requirements can be met by the use of smoothness-of-motion constraint. The s...

In this paper we use multiscale characteristics of wavelet decompositions and their relationship to smoothness spaces such as Besov spaces to derive a framework for smoothing and sharpening of signals and images. As a result, we derive a multiscale generalization of traditional techniques, such as unsharp masking, while using the smoothness parameter α in the Besov space Bα q (L p) to provide a...

Introduction: Filtering can greatly affect the quality of clinical images. Determining the best filter and the proper degree of smoothing can help to ensure the most accurate diagnosis. Methods: Forty five patient’s data aquired during brain phantom SPECT studies were reconstructed using filtered back-projection technique. The ramp, Shepp-Logan, Cosine, Hamming, Hanning, Butterworth, Metz...

Ill-conditioned or singular data modeling problems are commonly observed in image processing. To solve these problems some constraints, such as smoothness and boundary conditions have to be formulated. Further, the optimal structure of the model is not always self-evident. There are several criteria that can be applied for ”optimal” regularization gain or model selection. However, these measure...

used to estimate the ‘‘roughness’’ of a grey-level image, was replaced by a three-dimensional Laplacian, which also The problem addressed in this work is restoration of images that have several channels of information. We have studied incorporates between-channel smoothness. Also, the GCV color images so far, but hopefully the ideas presented here method for estimating the regularization parame...

This chapter presents the proposed color texture segmentation approach based on Reduced Biquaternions (RBs) and Discrete Wavelet Transform (DWT). Color and texture are the two essential features in color image analysis. The perception of color is of paramount importance in application areas such as multimedia, computer vision, graphics, biomedical signal processing, and industrial inspection. H...

In this paper, we propose a regularization technique for noisy-image super-resolution and image denoising. Total variation (TV) is adopted in many processing applications to preserve the local smoothness. However, TV prior prone oversmoothness, staircasing effect, contrast losses. Nonlocal (NLTV) mitigates losses by adaptively weighting smoothness based on similarity measure of patches. Althoug...

Uniform quantization of wavelet coefficients introduces perceptually disturbing artifacts by decreasing the visual smoothness. In this paper, the local Holder regularity is used to quantify these changes in visual smoothness. A modified uniform quantization scheme that constrains local regularity reduction is proposed. The quantizer modification is applicable to any uniform quantization scheme ...